DNAism: Exploring genomic datasets on the web with horizon charts

Computational biologists daily face the task of manipulating, sharing and communicating about large, intricate datasets produced by Next-Gen sequencing. Visual channels are an effective way to explore data but the accelerating increase in data quantity is pushing the limits of current approaches at representing these datasets without sacrificing accuracy or graphical perception. Data volume is increasing in one dimension as throughput per subject increases, and another as studies incorporate ever larger numbers of subjects. Thus, more effective visualization techniques may help manage the most challenging Next-Gen Sequencing datasets. Horizon Charts have proved to be an effective visualization approach when working with very large amounts of time-series encoded data. BED files are the gold standard for capturing genomic metrics in the Next-Gen sequencing domain. With time series, metrics are monitored over time, BED files use genomic coordinates instead. We have adapted a time series javascript library (cubism [1]) to the genomic domain. We call this new library DNAism.